InferEdge

Multi-repository entrypoint for the InferEdge local-first Edge AI inference validation pipeline.

InferEdge is not a benchmark-only script and not a production SaaS dashboard. It is a contract/preset based validation workflow that connects build provenance, real Runtime execution, validation evidence, optional deterministic diagnosis evidence, and Lab-owned deployment decisions.

The ecosystem is organized by lifecycle questions:

Can we deploy this model?                         -> InferEdge validation layer
Can this benchmark evidence be trusted and compared? -> InferEdgeEnv comparability layer
Can deployed workloads stay stable under load?   -> InferEdgeOrchestrator operation layer

ONNX Model
-> InferEdgeForge
-> InferEdge-Runtime
-> InferEdgeLab
-> optional InferEdgeAIGuard
-> Deployment Decision Report
-> Local Studio

Repositories

Repository	Role	URL
InferEdgeForge	Build provenance, metadata, manifest, artifact handoff	https://github.com/gwonxhj/InferEdgeForge
InferEdge-Runtime	C++ execution, Lab-compatible result JSON, Jetson evidence reports	https://github.com/gwonxhj/InferEdge-Runtime
InferEdgeLab	Compare/evaluate/report/API/Local Studio/deployment decision owner	https://github.com/gwonxhj/InferEdgeLab
InferEdgeAIGuard	Optional deterministic diagnosis evidence provider	https://github.com/gwonxhj/InferEdgeAIGuard

Ecosystem Extension Layers

These repositories extend the lifecycle beyond the pinned Core 4 validation message without replacing Forge, Runtime, Lab, or AIGuard.

Repository	Role	URL
InferEdgeEnv	v0.1.5 v1-complete comparability layer: local run evidence registry and benchmark evidence trust/comparison judgement	https://github.com/gwonxhj/InferEdgeEnv
InferEdgeOrchestrator	Operation layer after deployment validation: scheduling, overload control, and runtime telemetry	https://github.com/gwonxhj/InferEdgeOrchestrator

For the submission-ready diagram and layer split, start with InferEdge Ecosystem 1-Page Summary.

Quick Start

Clone this entrypoint repo first:

git clone https://github.com/gwonxhj/InferEdge.git
cd InferEdge

Clone all pipeline repositories:

bash scripts/clone_all.sh --locked

This creates:

repos/
├─ InferEdgeForge
├─ InferEdge-Runtime
├─ InferEdgeLab
└─ InferEdgeAIGuard

Run the portfolio smoke checks:

bash scripts/smoke_all.sh

Open the Local Studio demo:

cd repos/InferEdgeLab
poetry run inferedgelab serve --host 127.0.0.1 --port 8000

Then open:

http://127.0.0.1:8000/studio

Click Load Demo Evidence to replay the bundled ONNX Runtime CPU vs TensorRT Jetson evidence, compare view, deployment decision context, and optional AIGuard diagnosis cases.

Reproducible Clone Modes

Use the verified lock file:

bash scripts/clone_all.sh --locked

Use the latest main branch from each repo:

bash scripts/clone_all.sh --latest

Update existing clones:

bash scripts/update_all.sh --latest

or return to the locked portfolio snapshot:

bash scripts/update_all.sh --locked

Entrypoint Files

File	Purpose
repos.yaml	Human-readable repository map
repos.lock	Verified commit snapshot used by --locked
scripts/clone_all.sh	Clone all InferEdge Core repositories
scripts/update_all.sh	Update existing clones to latest or locked state
scripts/smoke_all.sh	Run cross-repo portfolio smoke checks
docs/ecosystem_1page.md	Submission-ready ecosystem diagram and three-question layer map
docs/assets/inferedge_ecosystem_diagram.svg	Reusable ecosystem diagram asset for README, portfolio pages, and slides
docs/portfolio_summary.md	30-second portfolio summary and one-line repository role map
docs/final_submission_rehearsal.md	Clean-clone submission gate rehearsal and results
docs/pipeline_map.md	Pipeline map and repository responsibility guide

Current Demo Evidence

The canonical Local Studio demo evidence is maintained in InferEdgeLab and InferEdge-Runtime:

Evidence	Value
TensorRT Jetson FP16 25W mean	10.066401 ms
TensorRT Jetson FP16 25W p99	15.548438 ms
TensorRT Jetson FP16 25W FPS	99.340373
ONNX Runtime CPU mean	45.4299 ms
ONNX Runtime CPU p99	49.2128 ms
ONNX Runtime CPU FPS	22.0119
Local Studio speedup	about 4.51x
YOLOv8 subset	10 images / 89 ground-truth boxes
simplified mAP@50	0.1410
precision / recall	0.2941 / 0.1685

Scope Boundary

Included:

• local-first validation workflow
• repository clone/update entrypoint
• Core 4 contract smoke orchestration
• Local Studio demo entrypoint
• README and documentation map

Not included:

• production SaaS infrastructure
• DB/Redis queue persistence
• auth/billing/upload flow
• cloud dashboard deployment
• automatic evaluation for arbitrary model families

Primary Review Path

For a reviewer or interviewer, start here:

1. docs/portfolio_summary.md
2. docs/final_submission_rehearsal.md
3. This README
4. docs/pipeline_map.md
5. repos/InferEdgeLab/README.md
6. repos/InferEdgeLab/docs/portfolio/inferedge_portfolio_submission.md
7. repos/InferEdge-Runtime/docs/reports/jetson_evidence_summary.md
8. repos/InferEdgeAIGuard/docs/detector_validation_matrix.md